Paper Authors

H. Bryan Riley
Ohio University

Dr. H. Bryan Riley, who joined Ohio University in 2010, has taught courses in signal processing, electrical communication systems, EE capstone design, electric machines, adaptive signal processing, and hybrid and electric vehicles. Riley, who spent his early career in the automotive industry, has managed multi-disciplined and global engineering teams responsible for introducing advanced electronic features on production passenger vehicles such as enhancements to vehicle stability control (VSC), adaptive cruise control (ACC), and other active safety features. He holds three patents and launched Provectus Technical Solutions, LLC, and engineering services company. Dr. Riley has implemented a Vehicle Modeling and Simulation Laboratory (VMSL) and current research interests include autonomous vehicle modeling and simulation, sensor fusion, parameter estimation, and machine learning.

Abstract

Development and integration of robust algorithms, software, and hardware systems for autonomous driving continues to be of paramount importance. The US Transportation Department is projecting” Self-Driving Cars Will Go Mainstream in 5 years”. Developers, manufacturers, system component suppliers, and on to the maintenance and modification of roadways continue to press forward to present and validate proven solutions that will be safe, reliable and user friendly. In the spirit of technology advancements, a major goal of this project is to investigate the utilization of infrared (IR) proximity sensor (i.e., λ = 870 ±70 nm) combined with the Raspberry Pi 2 single board computer to interface and mount functional capability on two remote-controlled (RC) vehicles and demonstrate autonomous following. These RCs are referred to as the “lead” and “host”. The proposed paper will describe the learning experiences and implementation of the Raspbian operating system utilizing Wi-Fi capability to transmit/receive intra-vehicle messages. The technical criteria for selecting the IR sensors, configuring the GPIO port, camera port and power are further described as the total system design was completed. Additional project work included designing a motor controller for a commercially available 7.4 VDC motor to fabricating mechanical brackets for mounting hardware on the RCs. As the team, gained success in finalizing a working design, it became evident that a more robust control rather than a “bang-bang” controller needed to be implemented to achieve a smoother RC rolling behavior as host RC track behind the lead RC. To that end, a proportional-integral (PI) control algorithm is implanted in Python 2.7 to provide a more plausible response and tracking-following performance. The paper concludes by presenting test data that validates successful system integration, RC host / RC following performance and set forth an embedded system to aid in solving of challenging tasks as self-driving vehicles will penetrate today’s consumer market. Lastly, as engineers preparing enter graduate school and ultimately the job market, reporting on this project enables us to design autonomous driving systems that will be safe and well-received by lay drivers as they operate on public roadways.

EndNote - RIS

TY - CPAPER
AB - Development and integration of robust algorithms, software, and hardware systems for autonomous driving continues to be of paramount importance. The US Transportation Department is projecting” Self-Driving Cars Will Go Mainstream in 5 years”. Developers, manufacturers, system component suppliers, and on to the maintenance and modification of roadways continue to press forward to present and validate proven solutions that will be safe, reliable and user friendly. In the spirit of technology advancements, a major goal of this project is to investigate the utilization of infrared (IR) proximity sensor (i.e., λ = 870 ±70 nm) combined with the Raspberry Pi 2 single board computer to interface and mount functional capability on two remote-controlled (RC) vehicles and demonstrate autonomous following. These RCs are referred to as the “lead” and “host”. The proposed paper will describe the learning experiences and implementation of the Raspbian operating system utilizing Wi-Fi capability to transmit/receive intra-vehicle messages. The technical criteria for selecting the IR sensors, configuring the GPIO port, camera port and power are further described as the total system design was completed. Additional project work included designing a motor controller for a commercially available 7.4 VDC motor to fabricating mechanical brackets for mounting hardware on the RCs. As the team, gained success in finalizing a working design, it became evident that a more robust control rather than a “bang-bang” controller needed to be implemented to achieve a smoother RC rolling behavior as host RC track behind the lead RC. To that end, a proportional-integral (PI) control algorithm is implanted in Python 2.7 to provide a more plausible response and tracking-following performance. The paper concludes by presenting test data that validates successful system integration, RC host / RC following performance and set forth an embedded system to aid in solving of challenging tasks as self-driving vehicles will penetrate today’s consumer market. Lastly, as engineers preparing enter graduate school and ultimately the job market, reporting on this project enables us to design autonomous driving systems that will be safe and well-received by lay drivers as they operate on public roadways.
AU - H. Bryan Riley
CY - Columbus, Ohio
DA - 2017/06/24
PB - ASEE Conferences
TI - IR Sensing Integrated with a Single Board Computer for Development and Demonstration of Autonomous Vehicle Following
UR - https://peer.asee.org/27421
ER -